The direct stream will fail the task if there is a problem with the kafka broker. Spark will retry failed tasks automatically, which should handle broker rebalances that happen in a timely fashion. spark.tax.maxFailures controls the maximum number of retries before failing the job. Direct stream isn't any different from any other spark task in that regard.
The question of what kind of monitoring you need is more a question for your particular infrastructure and what you're already using for monitoring. We put all metrics (application level or system level) into graphite and alert from there. I will say that if you've regularly got problems with kafka falling over for half an hour, I'd look at fixing that before worrying about spark monitoring... On Mon, Nov 9, 2015 at 12:26 PM, swetha <swethakasire...@gmail.com> wrote: > Hi, > > How to recover Kafka Direct automatically when the there is a problem with > Kafka brokers? Sometimes our Kafka Brokers gets messed up and the entire > Streaming job blows up unlike some other consumers which do recover > automatically. How can I make sure that Kafka Direct recovers automatically > when the broker fails for sometime say 30 minutes? What kind of monitors > should be in place to recover the job? > > Thanks, > Swetha > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Kafka-Direct-does-not-recover-automatically-when-the-Kafka-Stream-gets-messed-up-tp25331.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
